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Separate Neural Networks for Gains and Losses in Intertemporal Choice

An important and unresolved question is how human brain regions process information and interact with each other in intertemporal choice related to gains and losses. Using psychophysiological interaction and dynamic causal modeling analyses, we investigated the functional interactions between region...

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Autores principales: Zhang, Yang-Yang, Xu, Lijuan, Liang, Zhu-Yuan, Wang, Kun, Hou, Bing, Zhou, Yuan, Li, Shu, Jiang, Tianzi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6129240/
https://www.ncbi.nlm.nih.gov/pubmed/30088149
http://dx.doi.org/10.1007/s12264-018-0267-x
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author Zhang, Yang-Yang
Xu, Lijuan
Liang, Zhu-Yuan
Wang, Kun
Hou, Bing
Zhou, Yuan
Li, Shu
Jiang, Tianzi
author_facet Zhang, Yang-Yang
Xu, Lijuan
Liang, Zhu-Yuan
Wang, Kun
Hou, Bing
Zhou, Yuan
Li, Shu
Jiang, Tianzi
author_sort Zhang, Yang-Yang
collection PubMed
description An important and unresolved question is how human brain regions process information and interact with each other in intertemporal choice related to gains and losses. Using psychophysiological interaction and dynamic causal modeling analyses, we investigated the functional interactions between regions involved in the decision-making process while participants performed temporal discounting tasks in both the gains and losses domains. We found two distinct intrinsic valuation systems underlying temporal discounting in the gains and losses domains: gains were specifically evaluated in the medial regions, including the medial prefrontal and orbitofrontal cortices, and losses were evaluated in the lateral dorsolateral prefrontal cortex. In addition, immediate reward or punishment was found to modulate the functional interactions between the dorsolateral prefrontal cortex and distinct regions in both the gains and losses domains: in the gains domain, the mesolimbic regions; in the losses domain, the medial prefrontal cortex, anterior cingulate cortex, and insula. These findings suggest that intertemporal choice of gains and losses might involve distinct valuation systems, and more importantly, separate neural interactions may implement the intertemporal choices of gains and losses. These findings may provide a new biological perspective for understanding the neural mechanisms underlying intertemporal choice of gains and losses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12264-018-0267-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-61292402018-09-12 Separate Neural Networks for Gains and Losses in Intertemporal Choice Zhang, Yang-Yang Xu, Lijuan Liang, Zhu-Yuan Wang, Kun Hou, Bing Zhou, Yuan Li, Shu Jiang, Tianzi Neurosci Bull Original Article An important and unresolved question is how human brain regions process information and interact with each other in intertemporal choice related to gains and losses. Using psychophysiological interaction and dynamic causal modeling analyses, we investigated the functional interactions between regions involved in the decision-making process while participants performed temporal discounting tasks in both the gains and losses domains. We found two distinct intrinsic valuation systems underlying temporal discounting in the gains and losses domains: gains were specifically evaluated in the medial regions, including the medial prefrontal and orbitofrontal cortices, and losses were evaluated in the lateral dorsolateral prefrontal cortex. In addition, immediate reward or punishment was found to modulate the functional interactions between the dorsolateral prefrontal cortex and distinct regions in both the gains and losses domains: in the gains domain, the mesolimbic regions; in the losses domain, the medial prefrontal cortex, anterior cingulate cortex, and insula. These findings suggest that intertemporal choice of gains and losses might involve distinct valuation systems, and more importantly, separate neural interactions may implement the intertemporal choices of gains and losses. These findings may provide a new biological perspective for understanding the neural mechanisms underlying intertemporal choice of gains and losses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12264-018-0267-x) contains supplementary material, which is available to authorized users. Springer Singapore 2018-08-07 /pmc/articles/PMC6129240/ /pubmed/30088149 http://dx.doi.org/10.1007/s12264-018-0267-x Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Zhang, Yang-Yang
Xu, Lijuan
Liang, Zhu-Yuan
Wang, Kun
Hou, Bing
Zhou, Yuan
Li, Shu
Jiang, Tianzi
Separate Neural Networks for Gains and Losses in Intertemporal Choice
title Separate Neural Networks for Gains and Losses in Intertemporal Choice
title_full Separate Neural Networks for Gains and Losses in Intertemporal Choice
title_fullStr Separate Neural Networks for Gains and Losses in Intertemporal Choice
title_full_unstemmed Separate Neural Networks for Gains and Losses in Intertemporal Choice
title_short Separate Neural Networks for Gains and Losses in Intertemporal Choice
title_sort separate neural networks for gains and losses in intertemporal choice
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6129240/
https://www.ncbi.nlm.nih.gov/pubmed/30088149
http://dx.doi.org/10.1007/s12264-018-0267-x
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